Hilbert-Pair Shaped Resonator for Ku-Band Applications
Bibliographic record
Abstract
The Ku-Band is a crucial part of the electromagnetic spectrum widely employed in satellite communications, radar systems, and other high-frequency applications.To enhance the performance of Ku-Band devices, such as novel resonator structures have been investigated.The Hilbert Resonator has shown promise due to its unique characteristics.This paper introduces the Hilbert resonator and conducts a comprehensive literature review to highlight its potential applications, design methodologies, and performance advantages in the context of Ku-Band technologies for their unique propagation properties and high data rate capacity.The proposed resonator is developed based on the second iteration of Hilbert-shaped fractal geometry.The proposed resonator is developed from a number of unit cells to suit the applications of Ku-band systems.Therefore, five-unit cells are introduced; each unit cell is constructed from a pair of Hilbert curve geometry.This number is considered after a comprehensive parametric study to recognize the optimal required number of unit cells.The proposed design is printed on Roger substrate to occupy an area of 30×35mm 2 when coupled to a 50Ω microstrip line.It is good to mention that the proposed resonator shows S12 -17dB at 14.25GHz.Our work is developed using a numerical parametric study based on CST MWS to determine the optimal design.We validated the obtained results from the optimal design using HFSS numerical simulations.Finally, a great agreement is achieved between the simulated results based on the involved software packages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".